Effects of mild moxibustion on intestinal microbiome and NLRP3 inflammasome in rats with 5-fluorouracil-induced intestinal mucositis.

OBJECTIVE: The present study investigated how mild moxibustion treatment affects the intestinal microbiome and expression of NLRP3-related immune factors in a rat model of intestinal mucositis (IM) induced with 5-fluorouracil (5-Fu). METHODS: Forty male Sprague-Dawley rats were randomly divided into control, chemotherapy, moxibustion and probiotics groups. The IM rat model was established by intraperitoneal injection of 5-Fu. Mild moxibustion treatment and intragastric probiotic administration were provided once daily for 15 days. Tissue morphology, serum levels of inflammatory factors and the expression levels of tight junction proteins, caspase-1, gasdermin D and NLRP3 were evaluated in colon tissue, through hematoxylin and eosin staining, electron microscopy, enzyme-linked immunosorbent assay, Western blotting, quantitative real-time reverse transcription polymerase chain reaction and immunofluorescence. Gut microbiome profiling was conducted through 16S rRNA amplicon sequencing. RESULTS: Moxibustion and probiotic treatments significantly increased the expression levels of tight junction proteins, reduced cell apoptosis and the expression levels of caspase-1, gasdermin D and NLRP3; they also decreased the serum levels of tumor necrosis factor-α, interleukin (IL)-6, IL-1ß and IL-18, while increasing serum levels of IL-10. Moxibustion and probiotic treatments also corrected the reduction in α-diversity and ß-diversity in IM rats, greatly increased the proportion of the dominant bacterial genus Lactobacillus and reduced the abundance of the genera Roseburia and Escherichia in chemotherapy-treated rats to levels observed in healthy animals. We also found that these dominant genera were firmly correlated with the regulation of pyroptosis-associated proteins and inflammatory factors. Finally, moxibustion and probiotic treatments elicited similar effects in regulating intestinal host-microbial homeostasis and the expression of NLRP3 inflammasome-related factors. CONCLUSION: Moxibustion exerts its therapeutic effect on IM by ameliorating mucosal damage and reducing inflammation. Moreover, moxibustion modulates the gut microbiota, likely via decreasing the expression levels of the NLRP3 inflammasome.

Comparison of combined anterior-posterior approach versus posterior-only approach in neuromuscular scoliosis: a systematic review and meta-analysis.

PURPOSE: Neuromuscular scoliosis (NS) is a complicated spinal disorder, and it could be treated through posterior-only approach (POA) or combined anterior-posterior approach (APA), which one is better and how to choose the surgical tactic is still in controversy. So comparing POA with APA parameters in the treatment of NS is meaningful. METHODS: Database of PubMed, Embase and Cochrane Library was systematically searched, and the studies, which focus on the comparisons of POA and APA in the treatment of NS, were included. The meta-analysis was performed by RevMan 5.3. RESULTS: Seven retrospective studies with 602 patients were included in meta-analysis. In previous analysis, statistically significant differences were observed in the major parameters between APA and POA. However, the results of subgroup meta-analysis, which focused on the correction angle and loss angle to eliminate the influence of different preoperative angles, were tend to no difference between two groups, except loss angle of scoliosis (MD, 6.4; 95% CI - 0.19 to 13) and correction angle of pelvic obliquity (MD, - 3.44; 95% CI - 6.71 to - 0.17). CONCLUSIONS: Our meta-analysis suggested that POA was similar to APA in the correction of scoliosis in coronal and sagittal planes. However, APA had advantages in the correction of pelvic obliquity and decreasing the loss of angle between postoperation and follow-up in main scoliosis, whereas POA had advantages in operative time, blood loss, duration of hospital stay and complications. LEVEL OF EVIDENCE: Level II. These slides can be retrieved under Electronic Supplementary Material.

Automatic EEG artifact removal: a weighted support vector machine approach with error correction.

An automatic electroencephalogram (EEG) artifact removal method is presented in this paper. Compared to past methods, it has two unique features: 1) a weighted version of support vector machine formulation that handles the inherent unbalanced nature of component classification and 2) the ability to accommodate structural information typically found in component classification. The advantages of the proposed method are demonstrated on real-life EEG recordings with comparisons made to several benchmark methods. Results show that the proposed method is preferable to the other methods in the context of artifact removal by achieving a better tradeoff between removing artifacts and preserving inherent brain activities. Qualitative evaluation of the reconstructed EEG epochs also demonstrates that after artifact removal inherent brain activities are largely preserved.

EEG-based mental fatigue measurement using multi-class support vector machines with confidence estimate.

OBJECTIVE: Automatic measurement and monitoring of mental fatigue are invaluable for preventing mental-fatigue related accidents. We test an EEG-based mental-fatigue monitoring system using a probabilistic-based support vector-machines (SVM) method. METHODS: Ten subjects underwent 25-h sleep deprivation experiments with EEG monitoring. EEG data were segmented into 3-s long epochs and manually classified into 5 mental-fatigue levels, based on subjects' performance on an auditory vigilance task (AVT). Probabilistic-based multi-class SVM and standard multi-class SVM were compared as classifiers for distinguishing mental fatigue into the 5 mental-fatigue levels. RESULTS: Accuracy of the probabilistic-based multi-class SVM was 87.2%, compared to 85.4% using the standard multi-class SVM. Using confidence estimates aggregation, accuracy increased to 91.2%. CONCLUSIONS: Probabilistic-based multi-class SVM not only gives superior classification accuracy but also provides a valuable estimate of confidence in the prediction of mental fatigue level in a given 3-s EEG epoch. SIGNIFICANCE: The work demonstrates the feasibility of an automatic EEG method for assessing and monitoring of mental fatigue. Future applications of this include traffic safety and other domains where measurement or monitoring of mental fatigue is crucial.